Hello World Quotes

“using algorithms as a mirror to reflect the real world isn’t always helpful, especially when the mirror is reflecting a present reality that only exists because of centuries of bias.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“Because the future doesn’t just happen. We create it.”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“It’s rarely obvious what our data can do, or, when fed into a clever algorithm, just how valuable it can be. Nor, in turn, how cheaply we were bought.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“Whenever we use an algorithm – especially a free one – we need to ask ourselves about the hidden incentives. Why is this app giving me all this stuff for free? What is this algorithm really doing? Is this a trade I’m comfortable with? Would I be better off without it?”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“There is no such thing as a new idea. It is impossible. We simply take a lot of old ideas and put them into a sort of mental kaleidoscope. We give them a turn and they make new and curious combinations. We keep on turning and making new combinations indefinitely; but they are the same old pieces of colored glass that have been in use through all the ages.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“It’s a phenomenon known to psychologists as social proof. Whenever we haven’t got enough information to make decisions for ourselves, we have a habit of copying the behaviour of those around us.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“It’s like the saying among airline pilots that the best flying team has three components: a pilot, a computer and a dog. The computer is there to fly the plane, the pilot is there to feed the dog. And the dog is there to bite the human if it tries to touch the computer.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“How good is good enough? Once you’ve built a flawed algorithm that can calculate something, should you let it?”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“Well, there were a few items in someone’s basket that were linked to low claim rates. The most significant, he told me, the one that gives you away as a responsible, houseproud person more than any other, was fresh fennel.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“And in the UK, cameras mounted on vehicles that look like souped-up Google StreetView cars now drive around automatically cross-checking our likenesses with a database of wanted people.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“Even if there are some objective criteria that make one artwork better than another, as long as context plays a role in our aesthetic appreciation of art, it’s not possible to create a tangible measure for aesthetic quality that works for all places in all times. Whatever statistical techniques, or artificial intelligence tricks, or machine-learning algorithms you deploy, trying to use numbers to latch on to the essence of artistic excellence is like clutching at smoke with your hands.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“it’s not necessarily explicit prejudices that are causing these biased outcomes, so much as history repeating itself.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“The outcome is biased because reality is biased. More men commit homicides, so more men will be falsely accused of having the potential to murder.fn2”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“It’s a bit like asking the audience in Who Wants To Be A Millionaire? A room full of strangers will be right more often than the cleverest person you know. (The ‘ask the audience’ lifeline had a 91 per cent success rate compared to just 65 per cent for ‘phone a friend’.?)21 The errors made by many can cancel each other out and result in a crowd that’s wiser than the individual.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“you're not using the product; you are the product”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“People are less tolerant of an algorithm’s mistakes than of their own – even if their own mistakes are bigger.”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“Imagine you're sitting having dinner in a restaurant. At some point during the meal, your companion leans over and whispers that they've spotted Lady Gaga eating at the table opposite. Before having a look for yourself, you'll no doubt have some sense of how much you believe your friends theory. You'll take into account all of your prior knowledge: perhaps the quality of the establishment, the distance you are from Gaga's home in Malibu, your friend's eyesight. That sort of thing. If pushed, it's a belief that you could put a number on. A probability of sorts. As you turn to look at the woman, you'll automatically use each piece of evidence in front of you to update your belief in your friend's hypothesis Perhaps the platinum-blonde hair is consistent with what you would expect from Gaga, so your belief goes up. But the fact that she's sitting on her own with no bodyguards isn't, so your belief goes down. The point is, each new observations adds to your overall assessment. This is all Bayes' theorem does: offers a systematic way to update your belief in a hypothesis on the basis of the evidence. It accepts that you can't ever be completely certain about the theory you are considering, but allows you to make a best guess from the information available. So, once you realize the woman at the table opposite is wearing a dress made of meat -- a fashion choice that you're unlikely to chance up on in the non-Gaga population -- that might be enough to tip your belief over the threshold and lead you to conclude that it is indeed Lady Gaga in the restaurant. But Bayes' theorem isn't just an equation for the way humans already make decisions. It's much more important that that. To quote Sharon Bertsch McGrayne, author of The Theory That Would Not Die: 'Bayes runs counter to the deeply held conviction that modern science requires objectivity and precision. By providing a mechanism to measure your belief in something, Bayes allows you to draw sensible conclusions from sketchy observations, from messy, incomplete and approximate data -- even from ignorance.”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“in 1983, the psychologist Lisanne Bainbridge wrote a seminal essay on the hidden dangers of relying too heavily on automated systems.48 Build a machine to improve human performance, she explained, and it will lead – ironically – to a reduction in human ability.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“Then the pathologist takes over. It doesn’t matter if the machine is flagging cells that aren’t cancerous; the human expert can quickly check through and eliminate anything that’s normal. This kind of algorithmic pre-screening partnership not only saves a lot of time, it also bumps up the overall accuracy of diagnosis to a stunning 99.5 per cent.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“We don’t perceive each year as a fixed period of time; we experience each new year as a smaller and smaller fraction of the life we’ve lived.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“ZUCK: Yeah so if you ever need info about anyone at Harvard ZUCK: Just ask. ZUCK: I have over 4,000 emails, pictures, addresses … [REDACTED FRIEND’S NAME]: What? How’d you manage that one? ZUCK: People just submitted it. ZUCK: I don’t know why. ZUCK: They ‘trust me’ ZUCK: Dumb fucks1”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“They’re giving you an inoffensive way of passing the time.”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“The researchers argued that, whichever way you use it, their algorithm vastly outperforms the human judge.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“popularity is a quick way to insure yourself against disappointment.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“When police are in a place,’ Davies told me, ‘they detect more crime than they would have done otherwise. Even if an equal value of crime is happening in two places, the police will detect more in the place they were”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“Other studies have shown that men are treated more severely than women for the same crime,”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“the judge put more faith in the algorithm than in the agreement reached by the defence and the prosecution, rejected the plea bargain and doubled Zilly’s sentence from one year in county jail to two years in a state prison.”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“(The term ‘machine learning’ first came up in the ‘Power’ chapter, and we’ll meet many more algorithms under this particular canopy later, but for now it’s worth noting how grand that description makes it sound, when the algorithm is essentially the flowcharts you used to draw at school, wrapped up in a bit of mathematical manipulation.)”
― Hannah Fry, Hello World: How to be Human in the Age of the Machine

“This is all Bayes' theorem does: offers a systematic way to update your belief in a hypothesis on the basis of the evidence. It accepts that you can't ever be completely certain about the theory you're considering, but allows you to make a best guess from the information available”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms

“In my view, the best algorithms are the ones that take the human into account at every stage. The ones that recognize our habit of over-trusting the output of a machine, while embracing their own flaws and wearing their uncertainty proudly front and centre.”
― Hannah Fry, Hello World: Being Human in the Age of Algorithms